{"title":"ServerMore","authors":"Amoghavarsha Suresh, Anshul Gandhi","doi":"10.1145/3472883.3486979","DOIUrl":null,"url":null,"abstract":"Serverless computing allows customers to submit their jobs to the cloud for execution, with the resource provisioning being taken care of by the cloud provider. Serverless functions are often short-lived and have modest resource requirements, thereby presenting an opportunity to improve server utilization by colocating with latency-sensitive customer workloads. This paper presents ServerMore, a server-level resource manager that opportunistically colocates customer serverless jobs with serverful customer VMs. ServerMore dynamically regulates the CPU, memory bandwidth, and LLC resources on the server to ensure that the colocation between serverful and serverless workloads does not impact application tail latencies. By selectively admitting serverless functions and inferring the performance of black-box serverful workloads, ServerMore improves resource utilization on average by 35.9% to 245% compared to prior works; while having a minimal impact on the latency of both serverful applications and serverless functions.","PeriodicalId":91949,"journal":{"name":"Proceedings of the ... ACM Symposium on Cloud Computing [electronic resource] : SOCC ... ... SoCC (Conference)","volume":"65 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM Symposium on Cloud Computing [electronic resource] : SOCC ... ... SoCC (Conference)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3472883.3486979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

Serverless computing allows customers to submit their jobs to the cloud for execution, with the resource provisioning being taken care of by the cloud provider. Serverless functions are often short-lived and have modest resource requirements, thereby presenting an opportunity to improve server utilization by colocating with latency-sensitive customer workloads. This paper presents ServerMore, a server-level resource manager that opportunistically colocates customer serverless jobs with serverful customer VMs. ServerMore dynamically regulates the CPU, memory bandwidth, and LLC resources on the server to ensure that the colocation between serverful and serverless workloads does not impact application tail latencies. By selectively admitting serverless functions and inferring the performance of black-box serverful workloads, ServerMore improves resource utilization on average by 35.9% to 245% compared to prior works; while having a minimal impact on the latency of both serverful applications and serverless functions.
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